Snowflake commits $6 billion in Graviton compute and AI spend on AWS over five years, reflecting accelerating demand for data and AI workloads
DUBAI: Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced that it has signed a multi-year strategic collaboration agreement (SCA) <a href="https://middleeastdaily.net/menassah-signs-mou-with-perbadanan-kota-buku-to-expand-the-reach-of-emirati-books-in-the-malaysian-market/”>with Amazon Web Services (AWS) to accelerate enterprise agentic AI adoption to help joint customers worldwide build and deploy AI faster and more securely. As part of the expanded collaboration, Snowflake is making a $6 billion multi-year infrastructure commitment to AWS, its largest to date, reflecting the accelerating enterprise demand for AI and data workloads running on AWS.
Snowflake was founded on AWS eleven years ago, and that foundation has grown into one of enterprise software’s broadest and deepest collaborations. The majority of Snowflake’s customers run on AWS today, with AWS recognizing Snowflake as a leading partner driving global customer adoption. The latest agreement builds on this momentum with deeper product integrations across generative AI and agentic AI, expanded go-to-market through AWS Marketplace, and joint investments in customer success programs, workload migrations, and strategic industry solutions designed to help enterprises move from AI experimentation to production-scale outcomes.
“AI has generated enormous excitement, but for enterprises, the real challenge and opportunity is turning intelligence into action,” said Sridhar Ramaswamy, CEO of Snowflake. “We are moving into the era of the agentic enterprise, where AI systems don’t just answer questions, but help organizations reason over trusted data, coordinate workflows, and drive real business outcomes. With AWS, we are making it easier for enterprises to bring AI directly to governed data, so they can move faster, operate with greater clarity, and create measurable impact at scale.”
“Enterprises are rapidly moving from experimenting with AI to putting intelligent agents to work that drive real business outcomes,” said Matt Garman, CEO of AWS. “Snowflake has built on AWS since day one, and their deepened commitment to run on Graviton delivers the world-class performance, flexibility, and cost savings customers need to run data warehousing and AI workloads at scale.”
Bringing AI to Where Enterprise Data Lives
AI is only as powerful as the data behind it. The expanded collaboration is anchored in a technical architecture that brings foundation models directly to governed enterprise data, eliminating the complexity and risk of moving sensitive information between systems.
Snowflake Cortex AI enables customers to build and deploy AI applications for text-to-SQL, summarization, sentiment analysis, and entity extraction directly within their Snowflake environment. Enterprises are rapidly adopting these capabilities to run AI on trusted, governed data without moving it outside their secure perimeter. Snowflake leverages AWS Graviton processors, delivering significant price-performance improvements for customers, and utilizing high performance, GPU-accelerated Amazon EC2 instances for AI model training and inference.
Accelerating AI Adoption with AWS
Since Snowflake first became available in AWS Marketplace, customers have embraced it as the fastest path to procure and deploy Snowflake’s AI and data capabilities – surpassing $7 billion in lifetime sales and exceeding $2 billion in calendar year sales in 2025, more than doubling transaction growth year-over-year. The expanded SCA builds on that trajectory, scaling joint initiatives to help even more customers discover, procure, and deploy AI and data solutions through AWS Marketplace with simplified contracting, faster procurement.
Snowflake has also continued expanding its global footprint on AWS, with launches completed or underway in 10 new regions including New Zealand (Auckland), South Africa (Cape Town), Thailand (Bangkok), AWS European Sovereign Cloud, and others to help customers meet data residency requirements and deploy AI closer to where their business operates.
Customers Deploying AI on Governed Data
From startups to global enterprises, customers including Fetch and Hex use Snowflake on AWS to unify data, eliminate silos, and deploy AI applications and agents on governed data to drive measurable business impact.
“AI is deeply embedded in how Fetch builds and operates every day, and our work with Snowflake and AWS is strengthening that foundation,” said Daniel Block, General Manager of Revenue and Partnerships, Fetch. “With Snowflake Cortex AI, we’ve deployed a semantic agent that allows our sales teams to query campaign data in natural language and get instant insights. This enables faster, more informed decision-making across our business to deliver more value for our brand partners.”
“Snowflake on AWS is the foundation that many of our customers rely on to move fast with data,” said Caitlin Colgrove, Co-Founder and CTO, Hex. “For teams using Hex to explore, analyze, and build with AI, having that layer be secure, governed, and performant isn’t a nice-to-have it’s what makes enterprise AI adoption real.”
Snowflake and AWS will further demonstrate their shared vision for enterprise AI at Snowflake Summit 26.
Learn more about the power of Snowflake on AWS here.
Forward‑Looking Statements
This press release contains express and implied forward-looking statements, including statements regarding Snowflake’s business strategy, plans, opportunities, or priorities; Snowflake’s products, services, and technology offerings, including those that are under development or not generally available; market growth, trends, and competitive considerations; Snowflake’s vision, strategy, and expected benefits relating to AI and other emerging product areas; and the integration, interoperability, and availability of Snowflake’s products, services, and technology offerings with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forward-looking statements as predictions of future events.